Though industry experts say that the cost of fraud in the healthcare industry is somewhere between $67-$224 billion—in one year alone which is passed on to consumers in the form of higher premiums. Many healthcare insurers are reluctant to hire Special Investigative Units (SIU's) to identify and fight fraud because they are perceived as costly and a risk that could potentially expose the insurer to bad-faith lawsuits. SIU agents are usually made up of a team of highly trained investigators, with law enforcement background and have specialized training and experience in the investigation of suspect insurance claims submitted by healthcare providers for reimbursement. Traditional claims investigations take many hours to complete and experienced investigators generally command high salaries. Vast amounts of claim forms and medical documentation has to be sorted, studied, and compared to industry guidelines, annual coding updates, triannual CCI updates, national/international rules and regulations, as well as applicable state statutes, regulations, rules and program requirements for the investigator to arrive at an opinion as to whether fraud has been detected.
Accordingly, there is a need in the art for a method and system that enables an investigator to analyze data and to detect fraud much faster, saving time and money for insurance companies, SIU agents, Federal agencies (DHHS), federal government, adjusters, claims management and state departments.
There is also a need in the art for a method that generates output from the data analyzation that is flexible so that it can be provided to an expert witness for evaluation or sent to attorney or insurance carrier without unnecessary, privileged or confidential information.
There is a need in the art for a method and system that reduces labor-intensive responsibilities and lowers overall expenses of analyzing the data but maintains quality assurance capabilities.
There is a need in the art for a method and system that has the ability to analyze the data across multiple healthcare providers, unique physician/practitioner identification numbers (UPIN#s), national provider identifier numbers (NPI#s), tax identification numbers (TIN#s), locations, Durable Medical Equipment (DME) suppliers, patient/claimants, occurrences, procedures, diseases/conditions and provider charges.
There is a need in the art for a method and system that has the ability to analyze patterns within the data and to generate user-friendly reports and color-coded graphs/charts.
There is a need in the art for a method and system that allows a user to define rules that generate an alert or flag contemporaneously with the analyzation of the data when the data being analyzed meets the user-defined set of rules.
There is a need in the art for a method and system that is adaptable to a user's specialized areas of interest for specific investigative projects.
There is a need in the art for a method and system with a user reference library on instructions on the proper use of medical equipment and devices, clinic inspection techniques, manufacturer specs of diagnostic equipment, required OIG Physician Compliance Program information, appropriate medical record keeping requirements, definitions of HCPCS/CPT® and ICD-9/ICD-10 codes, which are relevant to the data analyzation and fraud detection.
There is also a need in the art for a method and system that is flexible to adapt to meet a healthcare provider, insurers, legal counsel, SIU and Federal Government needs in terms of generating output, access, flags, patterning and search criteria.
It is, therefore, to the effective resolution of the aforementioned problems and shortcomings of the prior art that the present invention is directed.
However, in view of the prior art at the time the present invention was made, it was not obvious to those of ordinary skill in the pertinent art how the identified needs could be fulfilled.